Biology subjects

Pesthy, O.

Publications and source records attributed to Pesthy, O..

8 recordsLinked to original sources

bioRxiv2026

Flexible belief updating drives the childhood advantage in statistical learning

Children often outperform adults in probabilistic statistical learning tasks, yet the mechanisms underlying this developmental advantage remain poorly understood. Here, we used eye-tracking measures of belief updating to examine how children and adults acquire and update predictions in a probabilistic sequence-learning task. Using the standard (oculomotor) reaction time measure, children showed stronger statistical learning than adults, replicating previous behavioral findings while revealing a more detailed profile of developmental differences in statistical learning. Critically, children updated their predictions more frequently: they were less likely to repeat previous predictions and more likely to shift their expectations in response to new input. Adults, in contrast, showed greater persistence, tending to maintain prior predictions even when those predictions were inconsistent with the underlying statistical structure. Despite these pronounced differences in updating behavior, the processing and use of prediction errors were remarkably similar across age groups. These findings indicate that developmental differences in statistical learning do not primarily arise from how prediction errors are computed, but rather from how prior beliefs and incoming information are weighted during belief updating. Childrens enhanced learning may therefore reflect reduced reliance on stable priors and greater sensitivity to current sensory evidence, supporting a more exploratory learning strategy. Adults, by contrast, appear to favor an exploitative strategy that stabilizes existing predictions but reduces flexibility in probabilistic environments. More broadly, the results suggest that developmental changes in statistical learning may reflect age-related differences in how readily learners revise their predictions in response to incoming evidence. By integrating sensitive oculomotor measures with analyses that probe the mechanisms underlying belief updating, the present study provides a more fine-grained account of how predictive learning changes across development and offers a framework for reconciling previously inconsistent developmental findings in statistical learning.

neuroscience↗

bioRxiv2026

Capturing learning on the fly: an eye-tracking method to quantify prediction errors and updating the prior

The ability to build predictive models of the environment fundamentally drives adaptive behavior. Yet, the real-time dynamics of how these internal models are formed and updated remain poorly understood. Conventional methods often rely on indirect, offline measures or noisy motor responses, limiting insight into the fine-grained computational processes underlying learning. Here, we introduce a generalizable, gaze-based analytical framework that directly tracks the trial-by-trial dynamics of expectation formation and updating. Applying this framework to an unsupervised probabilistic learning task, we categorized anticipatory saccades to dissociate prediction errors arising from environmental stochasticity from those reflecting an inaccurate internal model, and quantified how these predictions were iteratively revised. Learners differentiated between these error types: noise-driven errors were more likely to happen, and triggered less updates than errors reflecting insufficient knowledge of the regularity. At the same time, participants exhibited a strong preference to repeat their previous predictions. This repetition bias was amplified when predictions aligned with the underlying regularity, but was also present for non-aligned responses. Critically, updating depended more strongly on whether a prior belief was consistent with the tasks probabilistic structure than on whether the predicted stimulus matched the actual, presented stimulus. These findings suggest that statistical learning may not strongly be driven by errors; rather, it may rely on conservative updating with relatively low learning rate, or, on a Hebbian, repetition-based process. Our framework thus offers a dual contribution: a broadly applicable tool for quantifying real-time expectations, and evidence for a learning strategy that prioritizes model stability in noisy environments.

neuroscience↗

bioRxiv2025

Frontal theta synchronization facilitates the acquisition of new statistical regularities, evidenced by predictive eye movements

Frontal midline theta oscillations are key neural markers for learning, set-shifting, and adaptive behavior, signaling cognitive control and the reorganization of neural representations. The present study explored how these oscillations mediate the extraction and updating of statistical regularities. We delivered 6 Hz in-phase transcranial alternating current stimulation (tACS) or sham tACS, synchronizing frontal midline theta during an eye-tracking probabilistic sequence learning task designed to test cognitive flexibility and assess pre-stimulus gaze direction changes. A novel probabilistic sequence with a partially overlapping structure was introduced that allowed us to distinguish between the retention of old sequences and the acquisition of new ones. Following comparable statistical learning in both groups during the stimulation session, our results showed that tACS reduced the erroneous anticipations of previously learned regularities, and allowed participants to show anticipations corresponding to the previously learnt regularities while being able to anticipate novel regularities flexibly. These results suggest a role of frontal midline theta in the flexible rewiring of the mental representations of prior probabilistic structures, and in making predictions more accurate.

neuroscience↗

bioRxiv2025

Inhibiting the right dorsolateral prefrontal cortex selectively enhances unsupervised statistical learning

The brain must balance the automatic extraction of environmental regularities with top-down cognitive control, yet the causal neural mechanisms governing this interplay are debated. In particular, the hemispheric contributions of the dorsolateral prefrontal cortex (DLPFC) remain unresolved. Here, we applied inhibitory repetitive transcranial magnetic stimulation (rTMS) to the left, right, or bilateral DLPFC in 95 healthy adults during a probabilistic sequence learning task. We found that inhibiting the right and bilateral DLPFC significantly enhanced statistical learning compared to sham stimulation, while the left DLPFC stimulation group remained similar to sham. Contrary to the hypothesis that this competition is mediated by the suppression of existing knowledge, episodic memory performance was unaffected across all stimulation groups. These findings challenge a direct episodic gating mechanism and suggest the DLPFCs influence on statistical learning is hemisphere-dependent. As an alternative, we propose that right DLPFC inhibition shifts cognitive processing toward a more exploratory information-sampling strategy, a view supported by our finding of significantly greater reaction time variability in the right and bilateral stimulation groups. Together, our results provide causal evidence for a right-lateralized suppressive influence of the DLPFC on unsupervised learning and suggest its modulatory role is linked to information processing style rather than direct competition with episodic memory systems.

neuroscience↗

bioRxiv2024

Individual differences in probabilistic learning and updating predictive representations in individuals with obsessive-compulsive tendencies

Obsessive-compulsive (OC) tendencies involve intrusive thoughts and rigid, repetitive behaviours that also manifest at the subclinical level in the general population. The neurocognitive factors driving the development and persistence of the excessive presence of these tendencies remain highly elusive, though emerging theories emphasize the role of implicit information processing. Despite various empirical studies on distinct neurocognitive processes, the incidental retrieval of environmental structures in dynamic and noisy environments, such as probabilistic learning, has received relatively little attention. In this study, we aimed to unravel potential individual differences in implicit probabilistic learning and the updating of predictive representations related to OC tendencies in the general population. We conducted two independent online experiments (NStudy1 = 164, NStudy2 = 257) with young adults. Probabilistic learning was assessed using a reliable implicit visuomotor probabilistic learning task, which involved sequences with second-order non-adjacent dependencies. Our findings revealed that even among individuals displaying a broad spectrum of OC tendencies within a non-clinical population, implicit probabilistic learning remained remarkably robust. Furthermore, the results highlighted effective updating capabilities of predictive representations, which were not influenced by OC tendencies. These results offer new insights into individual differences in probabilistic learning and updating in relation to OC tendencies, contributing to theoretical, methodological, and practical approaches for understanding the maladaptive behavioural manifestations of OC disorder and subclinical tendencies.

neuroscience↗

bioRxiv2024

Enhancing Retrieval Capacity of the Predictive Brain through Dorsolateral Prefrontal Cortex Intervention

The ability to extract spatial or temporal regularities across experiences is crucial for skill development and predictive processes. The prefrontal cortex (PFC) plays a key role in modulating competitive memory systems, supporting declarative/episodic memory as opposed to statistical learning. This regulatory role may explain findings of improved acquisition and consolidation of statistical regularities following the suppression of dorsolateral PFC (DLPFC) by repetitive transcranial magnetic stimulation (rTMS). This raises a key question: Is access to models and prior statistical knowledge also modulated by the DLPFC? This preregistered study provides new insights by examining the role of the DLPFC in retrieving pre-existing knowledge of temporally distributed statistical regularities. Using a probabilistic learning task, healthy participants engaged in implicit statistical learning for 25 minutes. After a 24-hour consolidation period, participants received either 1 Hz rTMS or sham stimulation over the left, right, or bilateral DLPFC for 10 minutes before retesting. We found more effective access to statistical regularities in the bilateral DLPFC group compared to the sham group. Our results suggest that DLPFC suppression enhances the retrieval of statistical knowledge, particularly when interhemispheric compensatory mechanisms are prevented. These findings contribute to understanding competitive memory systems and offer implications for cognitive enhancement strategies.

neuroscience↗

bioRxiv2018

Explicit instruction differentially affects subcomponents of procedural learning and consolidation

Procedural memory facilitates the efficient processing of complex environmental stimuli and contributes to the acquisition of automatic behaviours and habits. Learning can occur intentionally or incidentally, yet, how the mode of learning affects procedural memory is still poorly understood. Importantly, procedural memory is a complex cognitive function composed of different subprocesses, including the acquisition and consolidation of statistical, frequency-based and sequential, order-based knowledge. Therefore, we tested how statistical and sequence knowledge develops during incidental versus intentional procedural memory formation and during consolidation. Seventy-four young adults performed either the uncued, incidental (N = 37) or the cued, intentional (N = 37) version of a probabilistic sequence learning task. Performance was retested after a 12-hour offline period, enabling us to test the effect of sleep on consolidation; therefore, half of the participants slept during the delay, while the other half had normal daily activity (PM-AM versus AM-PM design). The mode of learning (incidental versus intentional) had no effect on the acquisition of statistical knowledge, while intention to learn increased sequence learning performance. Consolidation was not affected by intention to learn: Both statistical and sequence knowledge was retained over the 12-hour delay, irrespective of the mode of learning and whether the delay included sleep or wake activity. These results suggest a time-dependent instead of sleep-dependent consolidation of both statistical and sequence knowledge. Our findings could contribute to a better understanding of how the mode of learning (intentional or incidental) affects procedural memory formation and consolidation.

neuroscience↗

bioRxiv2017

Deconstructing Procedural Memory: Different Learning Trajectories and Consolidation of Sequence and Statistical Learning

Procedural learning is a fundamental cognitive function that facilitates efficient processing of and automatic responses to complex environmental stimuli. Here, we examined training-dependent and off-line changes of two sub-processes of procedural learning: namely, sequence learning and statistical learning. Whereas sequence learning requires the acquisition of order-based relationships between the elements of a sequence, statistical learning is based on the acquisition of probabilistic associations between elements. Seventy-eight healthy young adults (58 females and 20 males) completed the modified version of the Alternating Serial Reaction Time task that was designed to measure Sequence and Statistical Learning simultaneously. After training, participants were randomly assigned to one of three conditions: active wakefulness, quiet rest, or daytime sleep. We examined off-line changes in Sequence and Statistical Learning as well as further improvements after extended practice. Performance in Sequence Learning increased during training, while Statistical Learning plateaued relatively rapidly. After the off-line period, both the acquired sequence and statistical knowledge was preserved, irrespective of the vigilance state (awake, quiet rest or sleep). Sequence Learning further improved during extended practice, while Statistical Learning did not. Moreover, within the sleep group, cortical oscillations and sleep spindle parameters showed differential associations with Sequence and Statistical Learning. Our findings can contribute to a deeper understanding of the dynamic changes of multiple parallel learning and consolidation processes that occur during procedural memory formation.

neuroscience↗